Hindsight: Similarity-Based Analytics for Mars Rover Drive Retrieval

2026-07-17

AI Summary

This work addresses the inefficiency and error-proneness in Mars rover operations stemming from fragmented multi-source data and heavy reliance on manual correlation during path planning and fault diagnosis. To bridge this gap, the authors propose Hindsight, a novel visual analytics system that explicitly externalizes operators’ intuitive, holistic spatiotemporal understanding of driving events into a structured query mechanism. By integrating similarity-driven retrieval, fusion of heterogeneous multi-source data, and interactive spatiotemporal event modeling, Hindsight enables unified cross-source analysis and shareable workflows. Preliminary user studies demonstrate that Hindsight effectively supports operators in correlating terrain, telemetry, and fault events within a single interface, significantly enhancing the efficiency of mission planning and diagnostic tasks.

Abstract

While Mars rover operators plan drives across hazardous Martian terrain and diagnose unexpected faults, the necessary information is distributed across separate systems and often reconstructed through manual correlation and memory. To address this challenge, we partnered with Mars rover operators at the NASA Jet Propulsion Laboratory to introduce Hindsight, a visual analytics system that unifies previously disparate rover drive data into a single workspace for search, comparison, and investigation. This paper presents a design study of the Hindsight application. The partnership revealed that operators reason about drives as holistic spatiotemporal episodes rather than discrete parameters. By externalizing operator intuition into an explicit visual query process, we argue that Hindsight transforms analysis into a structured, shareable workflow. Preliminary feedback from operators suggests Hindsight supports their ability to correlate terrain, telemetry, and fault events within a singleworkspace.

Problem

• Mars rover
• drive retrieval
• visual analytics
• fault diagnosis
• data integration

Innovation

• visual analytics
• similarity-based retrieval
• rover drive data
• spatiotemporal episodes
• human-AI collaboration